Better Driving and Recall When In-car Information Presentation Uses Situationally-Aware Incremental Speech Output Generation

Better Driving and Recall When In-car Information Presentation Uses Situationally-Aware Incremental Speech Output Generation
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当车内信息呈现使用情境感知增量语音输出生成时,可以更好地驾驶和回忆

DOI:
10.1145/2667317.2667332
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发表时间:
2014
期刊:
Proceedings of the 6th International Conference on Automotive User Interfaces and Interactive Vehicular Applications
影响因子:
--
通讯作者:
Timo Baumann
Timo Baumann
中科院分区:
--
文献类型:
--
作者:
Casey Kennington;Spyridon Kousidis;Timo Baumann

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驾驶员分心是驾驶员在主要任务(驾驶)和其他次要任务之间共享认知资源的结果。在保持对话的情况下,意识到驾驶条件的人类乘客可以在可能需要驾驶员更多注意的情况下选择中断他的讲话,但车载信息系统通常不会表现出这种敏感性。我们已经设计并测试了这样一个系统在驾驶模拟环境。与其他系统不同的是,我们的系统通过语音(日程表条目与预定会议)提供信息,但能够对来自环境的信号做出反应,在驾驶员需要完全专注于驾驶任务时中断,随后恢复其交付。分心是通过次级短期记忆任务来测量的。在这两项任务中,当系统不调整其语音时,驾驶员的表现明显较差,而当系统智能中断和恢复时,他们在控制条件(无并发任务)方面的表现同样出色。
It is established that driver distraction is the result of sharing cognitive resources between the primary task (driving) and any other secondary task. In the case of holding conversations, a human passenger who is aware of the driving conditions can choose to interrupt his speech in situations potentially requiring more attention from the driver, but in-car information systems typically do not exhibit such sensitivity. We have designed and tested such a system in a driving simulation environment. Unlike other systems, our system delivers information via speech (calendar entries with scheduled meetings) but is able to react to signals from the environment to interrupt when the driver needs to be fully attentive to the driving task and subsequently resume its delivery. Distraction is measured by a secondary short-term memory task. In both tasks, drivers perform significantly worse when the system does not adapt its speech, while they perform equally well to control conditions (no concurrent task) when the system intelligently interrupts and resumes.
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使用增量语音生成进行情境感知的车内信息呈现:更安全、更有效
DOI: --
发表时间: 2014
期刊: DM@EACL
影响因子: --
作者:
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